A lasting shift in the set point of a homeostatic system

Plasticity is probably the most widely used term in modern neurobiology, clearly not to be recommended as an effective keyword in literature searches in this field. In its rudimentary form, the notion of plasticity as a vehicle for memory appears already in pre-scientific times: Socrates depicted memory as an impression on wax tablet, too hard in slow learners and oversoft in the forgetful ones (Plato, Theaetetus). It is likely that this and similar "metaphors were used much earlier. In the scientific discipline of memory research, 'plasticity' was formally born at least twice. James (1890) brought it up in his "classic chapter on "habit: 'Plasticity... means the possession of a structure weak enough to yield to an influence, but strong enough not to yield all at once . Organic matter, especially nervous tissue, seems endowed with a very extraordinary degree of plasticity of this sort... the phenomena of habit in living beings are due to the plasticity of the organic materials of which their bodies are composed'. Half a century later, Konorski (1948) listed plasticity as one of the two metaprinciples that underlie the operation of the central nervous system. These principles are excitability (later renamed 'reactivity', Konorski 1967), which is the capacity to be activated by stimulation of receptive organs, and plasticity, the capacity to change reactive properties as a result of successive activation.

At about the same time, Hebb (1949) proposed how use-dependent "synaptic growth can subserve learning ("algorithm, "cell assembly), and Monne (1949) suggested that "protein synthesis allows for lasting neural remodelling in the formation of the "engram.1 These proposals are tenets of neurobiology to date. The current Zeitgeist is that "stimulus-induced regulation of "intracellular signal transduction cascades, which culminates in the modulation of gene expression ("immediate early genes) and hence in de novo protein synthesis, embodies use-dependent neuronal plasticity; and that much of this action takes place in the synapse. The relation of all this to memory is encapsulated in the synaptic plasticity and memory hypothesis: Activity-dependent synaptic plasticity is induced at appropriate synapses during memory formation, and is both necessary and sufficient for the information storage underlying the type of memory mediated by the brain area in which that plasticity is observed' (Martin et al. 2000).

This Zeitgeist deserves a caveat or two. But they will follow later. First, it is useful to consider briefly neural plasticity at multiple "levels of function and analysis. These are the theory level, the algorithmic level, and the implementational, or hardware level.

1. The theory level. In the theoretical world of all-possible organisms, it is not a given that adult individuals will show neural plasticity.2 That in real-life plasticity is the rule rather than the exception, is commonly attributed to the selective pressures of biological evolution. This means that the gain of adult plasticity outweighs the loss. The gain is clear: the ability to fine-tune the "a priori genetic adaptations, and hence survive in an even larger spectrum of mutable habitats. To this one could add the capacity to utilize only part of the potential gene products at one time, and also to amend injured cells and tissues. The loss is the metabolic price paid for the production of the plasticity machinery, and the risk that plasticity will go astray, resulting in malignancy or degeneration (indeed some authors consider "dementia to be a catastrophe of plasticity, e.g. Mesulam 1999). Another type of explanation, though, is that adult organisms are plastic because of built-in properties of biological material, and not because plasticity was selected for per se? This could be due to the ephemeral nature of the stuff of cells, plasticity being the by-product of the ability to replace continuously cellular components and correct mistakes in their production; or to opportunistic capitalization by evolution on processes that permit multicellular organisms to grow postnatally.

The above considerations refer to the overall principle of'adapt your behaviour to the world'. How is this achieved? The system follows a few computational rules, which refer to the probability of co-occurrence of events. It is methodologically legitimate to describe these rules as though they have a teleological rationale: if events tend to "coincide in time or place, then they are related, one can predict the other, and their "internal representations deserve to be "associated. If an event follows action, then this event has a significant probability to be caused by the action, and again, this apparent causality deserves to be encoded.4 These rules guide "classical conditioning and "instrumental conditioning, respectively, yet are relevant to other learning situations as well.

2. The algorithmic level. The synaptic postulate of Hebb (1949), noted above, which proposes that synaptic connections are "reinforced by coincident activity of pre- and postsynaptic terminals, is the one most discussed in the literature on neural and behavioural plasticity ["algorithm, "long-term potentiation (LTP)]. Additional algorithms at the circuit and system levels are illustrated in "algorithm, "dopamine, "instrumental learning.

3. The hardware level. How are the neural algorithms implemented? This is done by multiple types of cellular devices, which include "receptors, "ion channels, "neu-rotransmitter release machinery, "intracellular signal transduction cascades, "protein kinases, cytoskeletal elements, "immediate and "late response gene products.5 Among these are "coincidence detectors that operate on a variety of time-scales, and growth regulators. Each of these molecules is itself plastic. Pioneering work in identifying molecules of neural plasticity and their relevance to simple memory has been done on "Aplysia (Kandel 1976; Kandel and Schwartz 1982). Other systems, capable of "LTP, "habituation, "sensitization, and "classical conditioning, are also used extensively.

A recurrent issue in the field of neural plasticity is whether the same cellular machinery that subserves development also subserves learning and memory. Some authors emphasize the similarity (e.g. Martin and Kandel 1996), others the differences (e.g. Constantine-Paton and Cline 1998). It is noteworthy that developmental plasticity, in contradiction to long-held dogma, continues to function in the nervous system throughout life ("birdsong, "hippocampus; interestingly, simple physical activity could activate it; van Praag et al. 1999). Even if it does stop, it manages to affect markedly the "capacity of later use-dependent plasticity in the adult (e.g. Martin et al. 1991; Carvell and Simons 1996; Rosenzweig and Bennett 1996; Sylva 1997; Crair et al. 1998). Another point to remember is that components of the plasticity machinery in neurons are shared by non-neuronal tissues throughout development and in adulthood. This reinforces the notion, mentioned above, that plasticity is a universal biological property; it also supports, by the way, the conviction that cellular plasticity alone will not explain "memory.

The fact that the molecular biology of learning has become predominantly the molecular biology of synaptic plasticity, is an inevitable consequence of the "reductive approach to learning. The remarkable success in deciphering the mechanisms of synaptic plasticity should not, however, distract us from noting some caveats. First, it now becomes evident that the focus on the synapse has led to unjustified neglect of cell-wide processes and mechanisms (Frey and Morris 1997; Casadio et al. 1999; Dudai and Morris 2000). Second, the role of glia cells is still an "enigma, and breakthroughs should be expected on this frontier (Araque et al. 1999; Ullian et al. 2001). And third, most importantly, the crucial issue is whether neural plasticity, be it synaptic or cell-wide or both, is both necessary and sufficient ("criterion) for learning and memory. Ample evidence, much of which is cited in this book, indicates that neural plasticity is necessary for learning and memory; but a careful survey of the literature shows that few data currently support the notion that synaptic plasticity is sufficient for learning and memory to take place (Martin et al. 2000). To prove sufficiency, one should be able to induce artificially controlled plasticity in identified synapses that implement the specific, targeted internal representations. This is not easy, as it requires identification of circuits that encode specific internal representations, and of synapses that are critically important in these circuits. Examples of attempts to follow this line of research are mentioned in "method. Note that even if at the end of the day experiments of this type will indeed show that use-dependent synaptic plasticity is sufficient to register a specific memory, it will still remain to be determined how learning and memory processes are initiated in vivo; is it a bottom-up process, from the synaptic to higher levels, or is it a top-down process, in which higher-level activity initiates the plastic change in the appropriate synapses.

Selected associations: Development, Metaplasticity, Persistence, Reduction, Synapse

1Both Hebb (1949) and Monne (1949) drew, naturally, upon the work of others. The role of synaptic growth in learning has been discussed earlier (e.g. Cason 1925; 'development). The precedents of Hebb's synaptic postulate are discussed in 'algorithm. The proposal in Monne's paper was based on the pioneering work of contemporary research groups in cellular and chemical biology (e.g. Hamberger and Hyden 1945).

2In this discussion, plasticity (definitions 1 and 2), unless otherwise indicated, refers to neural plasticity. But most early authors, such as James (1890) and Semon (1904), aptly emphasized that plasticity, whether called by that name or not, is a universal property of the biological material.

3This argument fits the anti-Panglossian paradigm, see 'paradigm. 4No assumptions are being made here concerning 'conscious awareness of this potential causality, or the validity of the assumed causality. See also Macphail (1996) and Heyes and Huber (2000). 5This is an appropriate point to note that many authors distinguish functional from structural plasticity. The truth is that 'functional' plasticity also involves modification in some hardware component(s) of the system, hence is structural. It is all a matter of the level of 'reduction. What those who speak about structural plasticity mean, is morphological plasticity: those structural changes in the tissues that are detectable down to the level of electron microscopy (see example in 'development, Figure 25, p. 81).

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